Contrastive learning is a type of self-supervised representation learning method that is based on recognizing the similarities and differences between objects. The goal of contrastive learning is to group positive examples (similar samples) closer and separate negative examples (dissimilar samples), which can be treated as a specific type of pretext tasks [1]}.
